Deep machine learning potentials for multicomponent metallic melts: Development, predictability and compositional transferability

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
Original languageEnglish
Article number118181
Number of pages10
JournalJournal of Molecular Liquids
Volume349
DOIs
Publication statusPublished - 1 Mar 2022

Keywords

  • ab initio simulations
  • Al-Cu-Ni alloys
  • Machine learning potential
  • Molecular dynamics
  • Multicomponent melts
  • Neural networks
  • DENSITY
  • ALUMINUM
  • ACCURATE
  • APPROXIMATION
  • LIQUID
  • COPPER

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Materials Chemistry
  • Atomic and Molecular Physics, and Optics
  • Spectroscopy
  • Physical and Theoretical Chemistry

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